RNAseq

Quality check from Kallisto output

This information is to be coupled with the multiQC report generated by the pipeline. The percentage of pseudoaligned reads is more homogeneous and higher when the paired-end protocol is used. Looking at all the figures generated, the results seem to be of better quality when using the paired-end protocol.

Protocol

n_targets

n_processed

n_pseudoaligned

n_unique

p_pseudoaligned

p_unique

Protocol + Condition

n_targets

n_processed

n_pseudoaligned

n_unique

p_pseudoaligned

p_unique

Differental Expression : Treated vs Untreated

Single-end

Results :

  • DEGs number : 1931 (padj < 0.05)
  • Up-regulated in Treated condition : 1055
  • Down-regulated in Treated condition : 876
  • Positive logFC = up-regulated in Treated condition / down-regulated in Untreated condition
  • Negative logFC = up-regulated in Untreated condition / down-regulated in Treated condition

Dataset

Liste

Outlier

Heatmap

PCA

Expression

Volcano

Top20

TopHeatmap

MDplot

Paired-end

Results :

  • DEGs number : 3346 (padj < 0.05)
  • Up-regulated in Treated condition : 1773
  • Down-regulated in Treated condition : 1573
  • Positive logFC = up-regulated in Treated condition / down-regulated in Untreated condition
  • Negative logFC = up-regulated in Untreated condition / down-regulated in Treated condition

Dataset

Liste

Outlier

Heatmap

PCA

Expression

Volcano

Top20

TopHeatmap

MDplot

Comparaison Single-end vs Paired-end

Intersection of the DEA result

There are more differentially expressed transcripts detected between the treated and untreated conditions using the paired-end protocol. The paired-end protocol allows us to obtain both homogeneous samples and more biological information, as shown in the Kallisto output.

Furthermore, when a PCA is performed with the paired-end protocol, 97% of the dataset’s variability is explained by the treated/untreated feature, compared to 89% for the single-end protocol. This indicates that the biological variability of primary interest (the treatment effect) is much more highlighted and manageable with the paired-end protocol.

Due to the clarity and uniformity of the variability explained by the treatment condition in the paired-end protocol, the DEA results become more meaningful and easier to exploit. This may also explain why a greater number of differentially expressed transcripts are identified.

The paired-end protocol provides more biological information, which in turn offers greater statistical power, higher confidence in the results, and a clearer signal of the treatment effect compared to the single-end protocol.

Conversely, the single-end protocol introduces more noise into the results, making it less suitable for this type of analysis.

In conclusion, there is a clear treatment effect on the sequenced individuals, regardless of the protocol used. However, this effect is better highlighted when the paired-end protocol is employed.

Multivariate model (EXPERIMENTAL)

Dataset

Outlier

Heatmap

PCA

MDplot

Treated vs Untreated

Results :

  • DEGs number : 4106 (padj < 0.05)
  • Up-regulated in Treated condition : 2034
  • Down-regulated in Treated condition : 2072
  • Positive logFC = up-regulated in Treated condition / down-regulated in Untreated condition
  • Negative logFC = up-regulated in Untreated condition / down-regulated in Treated condition

Expression

Volcano

Top20

TopHeatmap

Single-end vs Paired-end

Results :

  • DEGs number : 5931 (padj < 0.05)
  • Up-regulated in Treated condition : 2457
  • Down-regulated in Treated condition : 3474
  • Positive logFC = up-regulated in Treated condition / down-regulated in Untreated condition
  • Negative logFC = up-regulated in Untreated condition / down-regulated in Treated condition

Expression

Volcano

Top20

TopHeatmap